An Artificial Intelligence Algorithm for Identifying Gynecologic Cancer Patients in Need of Outpatient Palliative Care

NCT ID: NCT06182332

Last Updated: 2025-04-04

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

221 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-12-11

Study Completion Date

2024-07-26

Brief Summary

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This clinical trial tests an artificial intelligence (AI) algorithm for its ability to identify patients who may benefit from a palliative care consult for gynecologic cancer that has spread from where it first started to nearby tissue, lymph nodes, or distant parts of the body (advanced). A significant delay in referral to palliative care often occurs among patients with cancer. This delay can lead to poorer symptom management, decreased quality of life, and care that does not align with patient goals or values. AI algorithms are computer programs that use step-by-step procedures to solve a problem. In this trial, an AI algorithm is applied to patients' medical records in order to identify patients with a high burden of disease. Information gathered from this study may help researchers learn whether this AI algorithm is useful for identifying patients who could benefit from outpatient palliative care consultation.

Detailed Description

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PRIMARY OBJECTIVE:

I. To pilot an oncology risk prediction model to identify patients who may benefit from outpatient palliative care consultation to improve symptom management and goal-concordant care in this population.

OUTLINE:

Patients' medical records are reviewed for consideration of palliative care consult using AI algorithm once a week (QW) for 6 months.

Conditions

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Advanced Malignant Female Reproductive System Neoplasm

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Screening (AI algorithm)

Patients' medical records are reviewed for consideration of palliative care consult using AI algorithm QW for 6 months.

Group Type EXPERIMENTAL

Electronic Health Record Review

Intervention Type OTHER

Undergo medical record review

Internet-Based Intervention

Intervention Type OTHER

Use AI algorithm

Interventions

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Electronic Health Record Review

Undergo medical record review

Intervention Type OTHER

Internet-Based Intervention

Use AI algorithm

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Adult patient in Enhanced, Electronic health record (EHR)-facilitated Cancer Symptom Control (E2C2) with a diagnosis of advanced gynecologic malignancy (International Classification of Diseases \[ICD\] codes C51 through C58)

Exclusion Criteria

* Patients that have been seen by palliative care will be excluded for 75 days
* Patients under the age of 18 years
* Patients currently enrolled with hospice
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Mayo Clinic

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Rachel D. Havyer, MD

Role: PRINCIPAL_INVESTIGATOR

Mayo Clinic in Rochester

Locations

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Mayo Clinic in Rochester

Rochester, Minnesota, United States

Site Status

Countries

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United States

Related Links

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Other Identifiers

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NCI-2023-09943

Identifier Type: REGISTRY

Identifier Source: secondary_id

23-008371

Identifier Type: OTHER

Identifier Source: secondary_id

23-008371

Identifier Type: -

Identifier Source: org_study_id

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